CHARACTERISATION OF STORM SEVERITY BY USE OF
SELECTED CONVECTIVE CELL PARAMETERS DERIVED FROM
SATELLITE DATA
Piotr Struzik
Institute of Meteorology and Water Management, Satellite Remote Sensing Centre
14 P. Borowego Str., 30-215 Krakow, Poland
Abstract
Rapid development of convective clouds leading to storm occurrence is a process which is still
investigated. Deep convection and storms are forecasted with significant uncertainty. In many cases,
storm severity cannot be predicted properly. An information characterising convective cell
development are required for storm monitoring, nowcasting and if lead time is sufficient, also for
warning.
Satellite data allow for monitoring of convection development from the early beginning. Presented
work is an analysis of main parameters characterising convection development connected with cloud
top features (i.e. overshooting tops and cloud top temperature) with relation to storm severity.
Application of thresholds determined outside Europe or even in different region of Europe leads
frequently to misinterpretation of the phenomena.
Storm severity cannot be determined by a simple indicator. There are many phenomena which
characterize storm severity: lightnings, precipitation intensity, hail occurrence, wind speed etc.. The
relation between thermal cloud top characteristics determined with use of: cloud top temperature and
overshooting tops occurrence (WV-IR temperature difference) to storm severity estimated by electrical
activity was analysed, taking into account recent storm seasons in Poland. In this study, electric
activity of storm cell determined from lightning detection system PERUN, operational in Poland, was
used as an indicator of storm severity. Additionally, comparison of observed at the ground Synop
―present weather‖ were compared to the occurrence of mentioned satellite derived cloud top features.
Obtained results were discussed to show benefits and limitations of this approach connected with
proper determination of cloud properties using satellite data and from the second hand appropriate
determination of storm severity with use of lightning detection. The purpose of this work was to
contribute to better determination of proper criteria for deep convection and storms analysis.
STORM SEVERITY – HOW WE CAN DEFINE IT?
Storm severity cannot be determined by a simple indicator. In the regions of tropical storms and
frequent tornadoes are used different scales. In such regions like Europe, storm severity is rather
related to meteorological phenomena, electric activity or damages resulted by: wind, hail, heavy
rainfalls, tornadoes. There are many features which can characterize storm:
 number of lightnings, type of lightnings (CC, CG-, CG+), maximum current,
 precipitation intensity, amount,
 hail occurrence, size,
 wind speed,
 tornado occurrence,
 damages.
The purpose of this study was to link storm occurrence and their severity observed at the ground with
features observed by satellites for further storm detection and its severity estimation.
Fig. 1. Manifestation of storm severity – left: results of tornado on 25.07.2007 (fot. IMWM), right:
lightnings (fot. R. Klejnowski)
SHORT DESCRIPTION OF ANALYSED SATELLITE AND GROUND OBSERVATIONS.
Most suitable for storm monitoring are those satellite products which can be for used 24 hours, not
related to Sun presence. Use of IR channels is in such case obligatory. Typical storm related satellite
products for 24 h storm monitoring are:
 IR 10.8 µm cloud top temperature and height,
 WV-IR temperature difference (called frequently Overshooting Tops Product),
 Cloud phase – use of 3.9 µm channel
 RGB colour composites,
 Combined products using several features (expert systems).
From the second hand available storm related ground observations are:
From Synop observations:
 wind,
 rain (6 hourly),
 actual weather, past weather:
Lightning detection systems:
 Lightning: type, position, current
Automatic weather stations:
 wind,
 rain (10 min),
Radars:
 Cloud droplets phase, hail detection,
 Cloud height,
 Radial wind based on Doppler measurements.
In this were used two satellite products, very popular for 24h storm detection and monitoring: clod top
temperature observed in IR 10.8 µm channel and observed temperature difference between WV 6.2
µm and IR 10.8 µm channels. As a ground reference, indicating, that we have storm, and
characterising storm severity were used: lightnings and Synop observations. Only cloud-to-ground
(CG) discharges from Polish PERUN system (SAFIR) were selected, due to several problems with
cloud-to-cloud (CC) lightnings. The last ones are frequently observed out of clouds (disturbances from
military aircrafts systems) and also have significant directional behaviour radial to ground stations. To
avoid additional errors CC lightnings were nor taken into account. Hourly Synop observation, with
synoptic code WW (Present Weather) were used to indicate storm occurrence, hail occurrence, storm
severity.
COMPARISON OF STORM CELL FEATURES AND DETECTED LIGHTNINGS.
Comparison between cloud features derived from satellite observations and lightnings detected by
ground system PERUN was performed for the whole 2010 storm season: 1.04-30.09.2010. One way
approach was analysed: if we have lightnings (storm exist) - what we can read from satellite data.
Opposite relation was still not analysed: if we have clouds with selected features (IR and WV-IR
temperatures) - does it mean, that we have storm ?
From lightning data were analysed: number of lightnings, type (CG+, CG-), current [kA]. To avoid
potential problems with parallax effect and localisation precision of PERUN system, satellite data from
the area surrounding discharge were taken into account. The box with size of 7x7 SEVIRI satellite
pixels were used for analysis. Such box centred over the lightning position lead to analysis of cloud
features within approximately 20 km radius (on the area of Poland). The minimum IR 10.8 temperature
and maximum WV-IR temperature from such box were used as an satellite indicators of cloud top
features.
The results from 2010 storm season are presented below. The number of lightnings detected for each
value of IR 10.8 Cloud Top Temperature.
Fig. 2. Number of lightnings, originating from clouds with presented top temperature.
It is well seen, that most of the lightnings are associated with cold clouds, approximately 90% of them
are connected with clouds having temperature between -48 and -72 deg. C. The coldest observed
cloud, which produced lightning had -72 deg. C. Much more frequent we can observe negative
discharges then positive ones. Only about 9% of cloud-to-ground lightnings had positive current.
For satellite products WV-IR, we observe opposite behaviour, majority of lightnings is associated with
WV-IR values close to 0 deg, specially positive discharges are most frequent when WV-IR
temperature difference is close or above zero.
Analysis of maximum current of CG lightnings with relation to cloud top properties visible by
METEOSAT SEVIRI instrument is presented on Fig.4. can be observed, that maximal currents are
connected with cold clouds. Less evident relation can be found on graph presenting lightnings
maximum current in relation to WV-IR temperature difference.
Fig. 3. Number of lightnings, originating from clouds with presented WV-IR temperature difference.
Fig.4. Maximum current of CG- and CG+ lightnings in comparison to Cloud Top Temperature and WVIR temp. Difference.
Such a behaviour of cloud electricity is not continuous during the whole storm season. At the
beginning of the season (April) and at the end (September) storm clouds are less developed, minimal
cloud top temperature found for those months is around -60 deg. C. Lightnings are more regularly
distributed over all cloud temperatures, specially for WV-IR graph. When middle part of storm season
was analysed, we can observe sharp maximum, both for IR and WV-IR cloud top properties.
Fig. 5. Seasonal differences - left: April and September, right: May, June, July, August 2010.
COMPARISON OF STORM CELL FEATURES AND OBSERVATIONS AT SYNOPTIC
POSTS.
Satellite products presenting derived cloud features, generated each 15 minutes from METEOSAT
satellite were compared to Synop observations. During whole 2010 storm season 1.04-30.09.2010
approx. 320 000 Synop reports from 76 Polish stations (including airport reports) were used for this
study. Satellite product from time slots xx:45 were used, as closest to Synop observation time.
Synoptic codes WW ―Present Weather‖ related to storm occurrence were used in analysis:
Non-Precipitation Events
13 -- Lightning Visible, No Thunder Heard
17 -- Thunderstorm But No Precipitation Falling At Station
18 -- Squalls Within Sight But No Precipitation Falling At Station – No Cases In 2010
19 -- Funnel Clouds Within Sight - No Cases In 2010
Precipitation Within Past Hour But Not At Observation Time
27 -- Hail Showers
29 -- Thunderstorms
Showers
89 -- light hail showers
90 -- moderate to heavy hail showers
Thunderstorms
91 -- Thunderstorm In Past Hour, Currently Only Light Rain
92 -- Thunderstorm In Past Hour, Currently Only Moderate To Heavy Rain
93 -- Thunderstorm In Past Hour, Currently Only Light Snow Or Rain/Snow Mix
94 -- Thunderstorm In Past Hour, Currently Only Moderate To Heavy Snow Or Rain/Snow Mix
95 -- Light To Moderate Thunderstorm
96 -- Light To Moderate Thunderstorm With Hail
97 -- Heavy Thunderstorm
98 -- Heavy Thunderstorm With Duststorm
99 -- Heavy Thunderstorm With Hail
Relation between Synop ―Present Weather‖ and both satellite derived IR 10.8 cloud top temperature
and WV-IR temp. difference were investigated. Box 7x7 SEVIRI satellite pixels centred over each
Synop station was used for analysis. Which is representation of approx 20 km horizon of storm
observations at the station (which may be not truth in the mountains). At the first analogically to the
study on lightnings, were counted reported Synop storm codes for each value of temperature (IR in 2
deg. steps WV-IR in 1 deg. Steps) – Fig. 6. Can be observed distinct maximum of reported storms
around cold cloud tops and around WV-IR close to 0 deg. C. Hypothesis, that those two features can
be used for storm detection is arousing.
Fig. 6. Number of reported Synop storm codes for each temperature value in 2010 storm season in
Poland.
Problem is becoming more difficult, when we analyse opposite relation and put on the graph also
Synop ―non-storm‖ cases. All synoptic WW codes were analysed, excluding only -1000 code, where
no indication of current weather is available.
Fig. 7. Number of Synop storm/non-storm reports for each value of IR 10.8 cloud top
temperature.
Can be observed, that only for very cold clouds and positive WV-IR temperature values
number of storm cases is higher than non-storm ones. Those two features were used as
indicator of storm. In the Table 1 are presented results in form of the contingency table. On
the left was used criteria, that storm cloud ought to have IR temperature below -48 deg. C
and WV-IR temp. difference above -3 deg. C.
Fig. 8. Number of Synop storm/non-storm reports for each value of WV-IR temperature difference.
Total = 32 031
POD = 0.64
FAR = 0.79
POFD = 0.10
Accuracy = 0.89
CSI = 0.19
Total = 34 219
POD = 0.40
FAR = 0.63
POFD = 0.03
Accuracy = 0.95
CSI = 0.24
Table 1-2. Contingency table with different criteria for storm features retrieved from satellite data.
Due to the high False Alarm Rate value, to reduce it, more sharp conditions were used on the right
side of Table 1 – cloud top temperature <=-53 deg. C and WV-IR >=0 deg. C. FAR was slightly
reduced, but also POD went down. Using only presented two cloud features is not possible to reduce
FAR. Additional method is required.
CONCLUSIONS.
1.
If we have lightnings, we can be sure, that most of them (90%) are produced by very cold
cloudes (-48 to -72 deg C on the area of Poland) and having WV-IR temperature difference
close or above 0 deg C.
2.
Majority of storms reported by Synop observations are connected with clouds having
presented above features.
3.
When we observe from space clouds having such a features, we cannot be sure that storms
are present (according to Synop records).
We still need additional parameters ! From space ?
But:
4.
So:
5.
6.
7.
We do not observe the same from space and on the ground.
More investigations are needed: comparison to Synop cloud observations, severe non-storm
weather, instantaneous precipitation from AWS, wind speed.
Reduction of FAR may be performed with use of additional information, radar products are the
most promising solution.
This study will be continued.
Determined convective cloud parameters were investigated for further use in automatic
expert system, under preparation at IMWM in frame of project: “Influence of climate
change to environment, economy and society”, co-financed by European Regional
Development Fund.
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